Open AccessCOHmax: an algorithm to maximise coherence in estimates of dynamic cerebral autoregulation
Author(s) -
Ronney B. Panerai,
Kannakorn Intharakham,
Jatinder S. Minhas,
Osian Llwyd,
Angela S. M. Salinet,
Emmanuel Katsogridakis,
Paola Maggio,
Thompson G. Robinson
Publication year - 2020
Publication title -
physiological measurement
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.674
H-Index - 101
eISSN - 1361-6579
pISSN - 0967-3334
DOI - 10.1088/1361-6579/aba67e
Subject(s) - normocapnia , hypercapnia , cerebral autoregulation , transcranial doppler , capnography , medicine , autoregulation , anesthesia , cerebral blood flow , hypocapnia , blood pressure , receiver operating characteristic , coherence (philosophical gambling strategy) , algorithm , mathematics , cardiology , statistics , acidosis
Objective : The reliability of dynamic cerebral autoregulation (dCA) parameters, obtained with transfer function analysis (TFA) of spontaneous fluctuations in arterial blood pressure (BP), require statistically significant values of the coherence function. A new algorithm (COH max ) is proposed to increase values of coherence by means of the automated, selective removal of sub-segments of data. Approach : Healthy subjects were studied at baseline (normocapnia) and during 5% breathing of CO 2 (hypercapnia). BP (Finapres), cerebral blood flow velocity (CBFV, transcranial Doppler), end-tidal CO 2 (EtCO 2 , capnography) and heart rate (ECG) were recorded continuously during 5 min in each condition. TFA was performed with sub-segments of data of duration (SEG D ) 100 s, 50 s or 25 s and the autoregulation index (ARI) was obtained from the CBFV response to a step change in BP. The area-under-the curve (AUC) was obtained from the receiver-operating characteristic (ROC) curve for the detection of changes in dCA resulting from hypercapnia. Main results : In 120 healthy subjects (69 male, age range 20–77 years), CO 2 breathing was effective in changing mean EtCO 2 and CBFV ( p < 0.001). For SEG D = 100 s, ARI changed from 5.8 ± 1.4 (normocapnia) to 4.0 ± 1.7 (hypercapnia, p < 0.0001), with similar differences for SEG D = 50 s or 25 s. Depending on the value of SEG D , in normocapnia, 15.8% to 18.3% of ARI estimates were rejected due to poor coherence, with corresponding rates of 8.3% to 13.3% in hypercapnia. With increasing coherence, 36.4% to 63.2% of these could be recovered in normocapnia ( p < 0.001) and 50.0% to 83.0% in hypercapnia ( p < 0.005). For SEG D = 100 s, ROC AUC was not influenced by the algorithm, but it was superior to corresponding values for SEG D = 50 s or 25 s. Significance : COH max has the potential to improve the yield of TFA estimates of dCA parameters, without introducing a bias or deterioration of their ability to detect impairment of autoregulation. Further studies are needed to assess the behaviour of the algorithm in patients with different cerebrovascular conditions.